Идиопатическое бесплодие: современные подходы к диагностике (обзор литературы)
Bibliographic record
Abstract
В статье представлен обзор современной научной литературы, посвященной проблеме изучения идиопатического бесплодия, и практических руководств под авторством ведущих мировых сообществ в сфере репродуктивной медицины: рекомендации CFAS (Канадское общество фертильности и андрологии), ASRM (Американское общество репродуктивной медицины), ESHRE (Европейское общество репродукции человека и эмбриологии). Описаны такие ключевые аспекты, как оценка функции яичников, оптимальные методы диагностики проходимости маточных труб, изучение состояния эндометрия с учетом его рецептивности, диагностика мужского фактора бесплодия и др. Рассмотрено потенциальное влияние на фертильность таких факторов, как микробиота влагалища, описана корреляция концентрации витамина D и исходов программ вспомогательных репродуктивных технологий. This article provides a comprehensive review of the latest scientific literature on idiopathic infertility and practical guidance from leading global reproductive medicine societies. The recommendations of the CFAS (Canadian Society of Fertility and Andrology), ASRM (American Society of Reproductive Medicine) and ESHRE (European Society of Human Reproduction and Embryology) are studied and analyzed. Therefore, the article provides a comprehensive overview of key aspects such as the assessment of ovarian function, optimal methods of diagnosing fallopian tube patency, the study of endometrium condition with regard to its receptivity, and the diagnosis of male factor infertility. It also considers the influence of vaginal microbiota on fertility and the correlation of vitamin D concentration with outcomes of assisted reproductive technology procedures.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.022 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".